Gedeck Peter, Lewis Richard A
Novartis Institutes for BioMedical Research, Novartis Horsham Research Centre, Wimblehurst Road, Horsham, West Sussex, RH12 5AB, UK.
Curr Opin Drug Discov Devel. 2008 Jul;11(4):569-75.
QSAR models can play a vital role in both the opening phase and the endgame of lead optimization. In the opening phase, there is often a large quantity of data from high-throughput screening (HTS), and potential leads need to be selected from several distinct chemotypes. In the endgame, the throughput of the final, critical ADMET and pharmacokinetic assays is often not sufficient to allow full experimental characterization of all the structures in the available time. A considerable amount of the current research toward new QSAR models is based on the modeling of the general ADMET phenomena, with the aim of constructing globally applicable models. The process to construct QSAR models is relatively straightforward; however, it is also simple to build misleading, or even incorrect, models. This review considers the key developments in the field of QSAR modeling: how QSAR models are constructed, how they can be validated, their reliability and their applicability. If applied carefully and appropriately, the QSAR technique has a valuable role to play during lead optimization.
定量构效关系（QSAR）模型在先导化合物优化的起始阶段和收官阶段都能发挥至关重要的作用。在起始阶段，通常会有大量来自高通量筛选（HTS）的数据，需要从几种不同的化学类型中筛选出潜在的先导化合物。在收官阶段，最终关键的药物代谢动力学及药物代谢、吸收、分布、排泄（ADMET）试验的通量往往不足以在可用时间内对所有结构进行全面的实验表征。当前针对新的QSAR模型的大量研究基于对一般ADMET现象的建模，目的是构建具有普遍适用性的模型。构建QSAR模型的过程相对简单；然而，构建误导性甚至错误的模型也很容易。本综述探讨了QSAR建模领域的关键进展：QSAR模型是如何构建的、如何进行验证、其可靠性以及适用性。如果谨慎且适当地应用，QSAR技术在先导化合物优化过程中能发挥重要作用。
